17 citations · 65 across the 51 of their papers we have counts for
11 papers · 1 filter
Joint Receive Antenna Selection and Beamforming in RIS-Aided MIMO Systems
Chongjun Ouyang, Ali Bereyhi, Saba Asaad +2
This work studies a low-complexity design for reconfigurable intelligent surface (RIS)-aided multiuser multiple-input multiple-output systems. The base station (BS) applies receive…
Statistical-CSI-Based Antenna Selection and Precoding in Uplink MIMO
Chongjun Ouyang, Ali Bereyhi, Saba Asaad +2
Classical antenna selection schemes require instantaneous channel state information (CSI). This leads to high signaling overhead in the system. This work proposes a novel joint rec…
A High-Level Comparison of Recent Technologies for Massive MIMO Architectures
Hans Rosenberger, Bernhard Gäde, Ali Bereyhi +6
Since the introduction of massive MIMO (mMIMO), the design of a transceiver with feasible complexity has been a challenging problem. Initially, it was believed that the main issue…
Analysis of Sparse Recovery Algorithms via the Replica Method
Ali Bereyhi, Ralf R. Müller, Hermann Schulz-Baldes
This manuscript goes through the fundamental connections between statistical mechanics and estimation theory by focusing on the particular problem of compressive sensing. We first…
How to Coordinate Edge Devices for Over-the-Air Federated Learning?
Mohammad Ali Sedaghat, Ali Bereyhi, Saba Asaad +1
This work studies the task of device coordination in wireless networks for over-the-air federated learning (OTA-FL). For conventional metrics of aggregation error, the task is show…
A Novel Antenna Placement Algorithm for Compressive Sensing MIMO Radar
Bastian Eisele, Ali Bereyhi, Ingrid Ullmann +1
In colocated compressive sensing MIMO radar, the measurement matrix is specified by antenna placement. To guarantee an acceptable recovery performance, this measurement matrix shou…
Matching Pursuit Based Scheduling for Over-the-Air Federated Learning
Ali Bereyhi, Adela Vagollari, Saba Asaad +3
This paper develops a class of low-complexity device scheduling algorithms for over-the-air federated learning via the method of matching pursuit. The proposed scheme tracks closel…
How Should IRSs Scale to Harden Multi-Antenna Channels?
Ali Bereyhi, Saba Asaad, Chongjun Ouyang +3
This work extends the concept of channel hardening to multi-antenna systems that are aided by intelligent reflecting surfaces (IRSs). For fading links between a multi-antenna trans…
Secure Coding via Gaussian Random Fields
Ali Bereyhi, Bruno Loureiro, Florent Krzakala +2
Inverse probability problems whose generative models are given by strictly nonlinear Gaussian random fields show the all-or-nothing behavior: There exists a critical rate at which…
Channel Hardening of IRS-Aided Multi-Antenna Systems: How Should IRSs Scale?
Ali Bereyhi, Saba Asaad, Chongjun Ouyang +3
Unlike active array antennas, intelligent reflecting surfaces (IRSs) are efficiently implemented at large dimensions. This allows for traceable realizations of large-scale IRS-aide…
Bayesian Inference with Nonlinear Generative Models: Comments on Secure Learning
Ali Bereyhi, Bruno Loureiro, Florent Krzakala +2
Unlike the classical linear model, nonlinear generative models have been addressed sparsely in the literature of statistical learning. This work aims to bringing attention to these…